Biometric authentication can be achieved by using any of the biometric data that can include, but not limited to, fingerprint, iris, face, retina, voice and the like. A typical biometric authentication system involves two main stages: enrollment and authentication. During enrollment, several biometric samples of a user are acquired and system registers the user by storing biometric information pertaining to the samples in the device's internal database. At the time of authentication, a biometric sample of the user is captured again and its biometric information is matched against the one stored in the database.
For instance, during fingerprint enrollment, several fingerprint images of the user are acquired; useful features are extracted and stored in the device's internal database. At the time of authentication, the user provides the fingerprint again. The system extracts features and matches them against the ones stored in the database. Although fingerprint enrollment is performed only once, it is a very crucial step as accuracy of authentication depends on the quality and completeness of enrolled samples.
Fingerprint authentication in current mobile devices is not limited to mere device unlocking but it is also used for high security applications such as mobile payments, securing sensitive information like health records, etc.
The use of embedded fingerprint sensors in mobile devices for authentication is prevalent. Typically, these sensors are miniaturized for cost and space constraints resulting in acquisition of partial fingerprints.
FIG. 1 is a schematic diagram 100 illustrating typical fingerprint sensor dimensions along with average fingerprint size according to the related art.
Referring to FIG. 1, the size of an average fingerprint 102 is about 0.5″×0.7″. But, the existing mobile devices primarily use rectangular shaped touch sensors 106 of size 0.45″×0.2″ or square shaped touch sensors 104 of size 0.2″×0.2″ approximately for fingerprint acquisition. Clearly, the platen area of these sensors is too small to capture entire finger thus requiring complex enrollment and matching methodology.
FIGS. 2A and 2B are schematic diagrams 200 illustrating enrollment and authentication process using finger scanning in user equipment (UE) 202 according to the related art.
Referring to FIG. 2A, during enrollment process, a user scans his finger on a small scanner present on the UE 202a. As the scanner present in the UE 202a is small, therefore plurality of images is scanned for the single finger. The plurality of scanned images are then combined to obtain a single fingerprint image using any of the known image generation techniques, such as, but not limited to, image stitching, and the like. The features extracted from the plurality of images are then stored as biometric information in an internal database 204a residing in the UE 202a. 
Referring to FIG. 2B, when the user wishes to access any of the services from UE 202b, then the user needs to be authenticated for accessing the service. During authentication, the same scanner from the UE 202b receives the fingerprint scan of the user's finger. Upon obtaining the fingerprint scan, the features are first extracted and compared against the features pertaining to fingerprint scans obtained during enrollment process stored in the database 204b to authenticate the user before allowing access to the services.
Solid-state fingerprint sensors present on equipment, such as, but not limited to mobile devices, tablet devices, PDA, laptop, and the like for acquiring fingerprints can be of type touch or swipe. As shown in FIG. 1, these sensors are miniaturized due to cost and space constraints which makes fingerprint enrollment and authentication on mobile devices complex procedures. In case of touch-based sensors, during enrollment, user is asked to provide multiple scans of the finger by lifting and touching the finger on the sensor in order to capture as much of finger portion possible. Although it is a one-time activity, it can be tedious and time-consuming. In case of swipe sensors, user needs to swipe finger multiple times during enrollment. Using overlapping partial scans, whole fingerprint is reconstructed using techniques like image stitching. This approach is proven to be underperforming since image stitching can be inaccurate and swiping finger on the sensor each time for authentication can be inconvenient especially for one-handed use of the mobile device.
Thus, there is a definite need for an improved method and system for faster, user-guided, and efficient biometric enrollment for mobile devices with small fingerprint sensors.
The above information is presented as background information only to assist with an understanding of the present disclosure. No determination has been made, and no assertion is made, as to whether any of the above might be applicable as prior art with regard to the present disclosure.